computational complexity; graph theory; parallel algorithms; Graphlab; MPBC; O(mn) time algorithm; O(n+m) space algorithm; O(nm+nlt; supgt; 2lt; /supgt; log n) time algorithm; SPBC; betweenness centrality metric; distributed algorithm; distributed computing; graph edges; graph vertices; information diffusion; key-vertex identification; large-scale graphs; message propagation; relative importance measure; shortest path approach; shortest paths; social networks; unweighted graphs; vertex-based parallel algorithm; vetex importance; weighted graphs; Algorithm design and analysis; Distributed algorithms; Mirrors; Parallel algorithms; Social network services; Synchronization; MPBC; SPBC; key vertices; parallel algorithm;
机译:提高不规则图的平行顶点为中心算法的效率
机译:提高并行顶点以不规则图形的算法效率
机译:梯形图上所有切点的最优顺序和并行算法
机译:识别大型图中关键顶点的以顶点为中心的并行算法
机译:大规模图分析的可扩展并行算法和实现。
机译:一种有效的算法用于计算与给定数量的顶点和自循环的树状图
机译:有界区间容差图中切割顶点,桥梁和哈密顿路径的最优并行算法